Model fit

Column

Assumption checks

Error: `check_model()` not implemented for models of class 'flexsurvreg' yet.

Column

Indices of model fit

'r2()' does not support models of class 'flexsurvreg'.
Metric Value
AIC 1.20e+05
BIC 1.20e+05
Sigma 0.00

For interpretation of performance metrics, please refer to this documentation.

Parameter estimates

Column

Plot

Package 'see' required for this function to work.package 'see' successfully unpacked and MD5 sums checked

The downloaded binary packages are in
    C:\Users\CISS Fondecyt\AppData\Local\Temp\Rtmpk5Vdeq\downloaded_packages
Error in plot.window(...): se necesitan valores finitos de 'ylim'

Column

Tabular summary

Fixed Effects
Parameter Coefficient SE 95% CI z p
mu 7.90 0.05 (7.79, 8.00) 151.46 < .001
sigma 0.88 0.02 (0.83, 0.93) 36.64 < .001
Q -1.28 0.06 (-1.39, -1.17) -22.78 < .001
tipo de plan res 1 (1) -0.64 0.03 (-0.71, -0.57) -18.74 < .001
TD 1 (1) 0.63 0.04 (0.55, 0.71) 15.27 < .001

To find out more about table summary options, please refer to this documentation.

Predicted Values

Column

Plot

Error in theme_modern(): could not find function "theme_modern"
Package 'see' required for this function to work.package 'see' successfully unpacked and MD5 sums checked

The downloaded binary packages are in
    C:\Users\CISS Fondecyt\AppData\Local\Temp\Rtmpk5Vdeq\downloaded_packages
Error in xy.coords(x, y, xlabel, ylabel, log): 'x' is a list, but does not have components 'x' and 'y'
Error in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]): namespace 'ggplot2' 3.3.5 is already loaded, but >= 3.3.6 is required

Column

Tabular summary

Model-based Expectation
tipo_de_plan_res_1 TD_1 .time .pred
0.00 0.00 Inf 0.13
1.00 0.00 Inf 0.14

Variable predicted: Surv(time, status)

Predictors modulated: tipo_de_plan_res_1

Model-based Expectation
TD_1 tipo_de_plan_res_1 .time .pred
0.00 0.00 Inf 0.13
1.00 0.00 Inf 0.12

Variable predicted: Surv(time, status)

Predictors modulated: TD_1

Text reports

Column

Textual summary

Error in report(model): could not find function "report"
Error in report_performance(model): could not find function "report_performance"
Error in is.factor(x): object 'text_report' not found
Error in is.factor(x): object 'text_report_performance' not found

Column

Model information

---
title: "Regression model summary from `{easystats}`"
output: 
  flexdashboard::flex_dashboard:
    theme:
      version: 4
      # bg: "#101010"
      # fg: "#FDF7F7" 
      primary: "#0054AD"
      base_font:
        google: Prompt
      code_font:
        google: JetBrains Mono
params:
  model: model
  check_model_args: check_model_args
  parameters_args: parameters_args
  performance_args: performance_args
---

```{r setup, include=FALSE}
library(flexdashboard)
library(easystats)

# Since not all regression model are supported across all packages, make the
# dashboard chunks more fault-tolerant. E.g. a model might be supported in
# `{parameters}`, but not in `{report}`.
#
# For this reason, `error = TRUE`
knitr::opts_chunk$set(
  error = TRUE,
  out.width = "100%"
)
```

```{r}
# Get user-specified model data
model <- params$model

# Is it supported by `{easystats}`? Skip evaluation of the following chunks if not.
is_supported <- insight::is_model_supported(model)

if (!is_supported) {
  unsupported_message <- sprintf(
    "Unfortunately, objects of class '%s' are not yet supported in {easystats}.\n
    For a list of supported models, see `insight::supported_models()`.",
    class(model)[1]
  )
}
```


Model fit 
=====================================  

Column {data-width=700}
-----------------------------------------------------------------------

### Assumption checks

```{r check-model, eval=is_supported, fig.height=10, fig.width=10}
check_model_args <- c(list(model), params$check_model_args)
do.call(performance::check_model, check_model_args)
```

```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=300}
-----------------------------------------------------------------------

### Indices of model fit

```{r, eval=is_supported}
# `{performance}`
performance_args <- c(list(model), params$performance_args)
table_performance <- do.call(performance::performance, performance_args)
print_md(table_performance, layout = "vertical", caption = NULL)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

For interpretation of performance metrics, please refer to <a href="https://easystats.github.io/performance/reference/model_performance.html" target="_blank">this documentation</a>.

Parameter estimates
=====================================  

Column {data-width=550}
-----------------------------------------------------------------------

### Plot

```{r dot-whisker, eval=is_supported}
# `{parameters}`
parameters_args <- c(list(model), params$parameters_args)
table_parameters <- do.call(parameters::parameters, parameters_args)

plot(table_parameters)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=450}
-----------------------------------------------------------------------

### Tabular summary

```{r, eval=is_supported}
print_md(table_parameters, caption = NULL)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

To find out more about table summary options, please refer to <a href="https://easystats.github.io/parameters/reference/model_parameters.html" target="_blank">this documentation</a>.


Predicted Values
=====================================  

Column {data-width=600}
-----------------------------------------------------------------------

### Plot

```{r expected-values, eval=is_supported, fig.height=10, fig.width=10}
# `{modelbased}`
int_terms <- find_interactions(model, component = "conditional", flatten = TRUE)
con_terms <- find_variables(model)$conditional

if (is.null(int_terms)) {
  model_terms <- con_terms
} else {
  model_terms <- clean_names(int_terms)
  int_terms <- unique(unlist(strsplit(clean_names(int_terms), ":", fixed = TRUE)))
  model_terms <- c(model_terms, setdiff(con_terms, int_terms))
}

text_modelbased <- lapply(unique(model_terms), function(i) {
  grid <- get_datagrid(model, at = i, range = "grid", preserve_range = FALSE)
  estimate_expectation(model, data = grid)
})

ggplot2::theme_set(theme_modern())
# all_plots <- lapply(text_modelbased, function(i) {
#   out <- do.call(visualisation_recipe, c(list(i), modelbased_args))
#   plot(out) + ggplot2::ggtitle("")
# })
all_plots <- lapply(text_modelbased, function(i) {
  out <- visualisation_recipe(i, show_data = "none")
  plot(out) + ggplot2::ggtitle("")
})

see::plots(all_plots, n_columns = round(sqrt(length(text_modelbased))))
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=400}
-----------------------------------------------------------------------

### Tabular summary

```{r, eval=is_supported, results="asis"}
for (i in text_modelbased) {
  tmp <- print_md(i)
  tmp <- gsub("Variable predicted", "\nVariable predicted", tmp)
  tmp <- gsub("Predictors modulated", "\nPredictors modulated", tmp)
  tmp <- gsub("Predictors controlled", "\nPredictors controlled", tmp)
  print(tmp)
}
```


```{r, eval=!is_supported}
cat(unsupported_message)
```


Text reports
=====================================    

Column {data-width=500}
-----------------------------------------------------------------------

### Textual summary

```{r, eval=is_supported, results='asis', collapse=TRUE}
# `{report}`
text_report <- report(model)
text_report_performance <- report_performance(model)

gsub("]", ")", gsub("[", "(", text_report, fixed = TRUE), fixed = TRUE)
cat("\n")
gsub("]", ")", gsub("[", "(", text_report_performance, fixed = TRUE), fixed = TRUE)
```


```{r, eval=!is_supported}
cat(unsupported_message)
```

Column {data-width=500}
-----------------------------------------------------------------------

### Model information

```{r, eval=is_supported}
model_info_data <- insight::model_info(model)

model_info_data <- datawizard::data_to_long(as.data.frame(model_info_data))

DT::datatable(model_info_data)
```

```{r, eval=!is_supported}
cat(unsupported_message)
```